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Chetty et al. (2022) say county density of cross-class friendships (referred to here as “adult-bridging capital”) has causal impacts on social mobility within the United States. We instead find that social mobility rates are a function of county density of family capital (higher marriage rates and two-person households), community capital (community organizations, religious congregations, and volunteering), and mean student achievement in grades 3-8. Our models use similar multiple regression equations and the same variables employed by Chetty et al. but also include state fixed effects, student achievement, and family, community, school-bridging (cross-class high school friendships), and political (participation and institutional trust) capital. School-bridging capital is weakly correlated with mobility if adult-bridging is excluded from the model. R-squared barely changes when adult-bridging is incorporated into the model. When it is included, mobility continues to be significantly correlated with the achievement, family, and community variables but not with school-bridging and political ones. We infer that county mobility rates are largely shaped by parental presence, community life, and student achievement. To enhance mobility, public policy needs to enhance the lives of disadvantaged people at home, in school, and in communities, not just the social class of their friendships.
The media discourse on student loans plays a significant role in the way that policy actors conceptualize challenges and potential solutions related to student debt. This study examines the racialized language in student loan news articles published in eight major news outlets between 2006 and 2021. We found that 18% of articles use any racialized language, though use has accelerated since 2018. This increase appears to be driven by terms that denote groups of people instead of structural problems, with 8% of articles mentioning “Black” but less than 1% mentioning “racism.” These findings emphasize the importance of treating the media as a policy actor capable of shaping the salience of racialization in discussions about student loans.
U.S. public school students increasingly attend schools with sworn law enforcement officers present. Yet, little is known about how these school resource officers (SROs) affect school environments or student outcomes. Our study uses a fuzzy regression discontinuity (RD) design with national school-level data from 2014 to 2018 to estimate the impacts of SRO placement. We construct this discontinuity based on the application scores for federal school based policing grants of linked police agencies. We find that SROs effectively reduce some forms of violence in schools, but do not prevent gun-related incidents. We also find that SROs intensify the use of suspension, expulsion, police referral, and arrest of students. These increases in disciplinary and police actions are consistently largest for Black students, male students, and students with disabilities.
Graduating from college into a recession is associated with earnings losses, but less is known about how these effects vary across colleges. Using restricted-use data from the National Survey of College Graduates, we study how college quality influences the effects of graduating into worse economic conditions in the context of the Great Recession. We find that earnings losses are concentrated among graduates from relatively high-quality colleges. Key mechanisms include substitution out of the labor force and into graduate school, decreased graduate degree completion, and differences in the economic stability of fields of study between graduates of high- and low-quality colleges.
The Core Knowledge curriculum is a K-8 curriculum focused on building students General Knowledge about the world they live in that is hypothesized to increase reading comprehension and Reading/English-LA achievement. This study utilizes an experimental design to evaluate the long term effects of attending Charter schools teaching the Core Knowledge curriculum. Fourteen oversubscribed kindergarten lotteries for enrollment in nine Core Knowledge Charter schools using the curriculum had 2310 students applying from parents in predominately middle/high income school districts. State achievement data was collected at 3rd- 6th grade in Reading/English-LA and Mathematics and at 5th Grade in Science. A new methodology addresses two previously undiscovered sources of bias inherent in kindergarten lotteries that include middle/high income families. The unbiased confirmatory Reading-English-LA results show statistically significant ITT (0.241***) and TOT (0.473***) effects for 3rd-6th grade achievement with statistically significant ITT and TOT effects at each grade. Exploratory analyses also showed significant ITT (0.15*) and TOT (0.300*) unbiased effects at 5th grade in Science. A CK-Charter school in a low income school district also had statistically significant, moderate to large unbiased ITT and TOT effects in English Language Arts (ITT= 0.944**; TOT = 1.299**), Mathematics (ITT= 0.735*; TOT = 0.997*) and positive, but insignificant Science effects (ITT= 0.468; TOT = 0.622) that eliminated achievement gaps in all subjects.
Broadband is not equally accessible among students despite its increasing importance to education. We investigate the relationship between broadband and housing policy by joining two measures of broadband access with Depression-era redlining maps that classified neighborhoods based in part on racist and classist beliefs. We find that despite internet service provider selfreports of similar technological availability, broadband access generally decreases in tandem with historic neighborhood classification, with further heterogeneity by race/ethnicity and income. Our findings demonstrate how past federally-developed housing policies connect to the digital divide and should be considered in educational policies that require broadband for success.
Inequality related to standardized tests in college admissions has long been a subject of discussion; less is known about inequality in non-standardized components of the college application. We analyzed extracurricular activity descriptions in 5,967,920 applications submitted through the Common Application platform. Using human-crafted keyword dictionaries combined with text-as-data (natural language processing) methods, we found that White, Asian American, high-SES, and private school students reported substantially more activities, more activities with top-level leadership roles, and more activities with distinctive accomplishments (e.g., honors, awards). Black, Latinx, Indigenous, and low-income students reported a similar proportion of activities with top-level leadership positions as other groups, although the absolute number was lower. Gaps also lessened for honors/awards when examining proportions, versus absolute number. Disparities decreased further when accounting for other applicant demographics, school fixed effects, and standardized test scores. However, salient differences related to race and class remain. Findings do not support a return to required standardized testing, nor do they necessarily support ending consideration of activities in admissions. We discuss reducing the number of activities that students report and increasing training for admissions staff as measures to strengthen holistic review.
Books shape how children learn about society and norms, in part through representation of different characters. We introduce new artificial intelligence methods for systematically converting images into data and apply them, along with text analysis methods, to measure the representation of skin color, race, gender, and age in award-winning children’s books widely read in homes, classrooms, and libraries over the last century. We find that more characters with darker skin color appear over time, but the most influential books persistently depict characters with lighter skin color, on average, than other books, even after conditioning on race; we also find that children are depicted with lighter skin than adults on average. Relative to their growing share of the U.S. population, Black and Latinx people are underrepresented in these same books, while White males are overrepresented. Over time, females are increasingly present but appear less often in text than in images, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. We then present analysis of the supply of, and demand for, books with different levels of representation to better understand the economic behavior that may contribute to these patterns. On the demand side, we show that people consume books that center their own identities. On the supply side, we document higher prices for books that center non-dominant social identities and fewer copies of these books in libraries that serve predominantly White communities. Lastly, we show that the types of children's books purchased in a neighborhood are related to local political beliefs.
This paper conceptualizes segregation as a phenomenon that emerges from the intersection of public policy and individual decision-making. Contemporary scholarship on complex decision-making describes a two-step process—1) Editing and 2) Selection— and has emphasized the individual decision-maker’s agency in both steps. We build on this work by exploring, both theoretically and empirically, how policy can structure the choices individuals face at each step. We conduct this exploration within the empirical context of enrollment decisions among families in the Wake County Public School System (WCPSS), which used a controlled school choice system to help achieve diversity aims. We first investigate the schooling choice sets that WCPSS constructed for families and then examine families’ schooling selections. We find that families were offered choice sets containing schools varying racial compositions, but that the racial makeup of schools in families’ choice set systematically varied by schooling type and student race/ethnicity. We further show that a majority of families enrolled in their district-assigned default school, with Black and Hispanic families more likely than white or Asian families to attend this option. Finally, we demonstrate that white or Asian families enroll in their default school at lower rates as the share of Black students increases.
How progressive is school spending when spending is measured at the school-level, instead of the district-level? We use the first dataset on school-level spending across schools throughout the United States to ask to what extent progressivity patterns previously examined across districts are amplified, nullified, or reversed, upon disaggregation to schools. We find that progressivity is systematically greater when we conduct a school-level analysis, rather than district-level analysis. This may be surprising, given the traditional view in public economics that local governments cannot effectively redistribute. We thus probe the data for explanations for this pattern, uncovering evidence that federal policies play an important role in driving within-district progressive allocations. In particular, we can explain about 83% of the within-district contribution to progressivity by the federal component of spending plus allocations that are empirically attributable to special education and English language learning programs. Our findings are thus consistent with the traditional view of redistribution being primarily the purview of central governments, operationalized in this context through mandates.